Finding, hiring, and retaining the best talent is tough. Technology has made extensive amounts of candidate information available to recruiters and hiring managers, but digging through all of that data is time consuming. Big data, an analytical approach to aggregating and analyzing massive amounts of data for trends, is changing the way businesses hire talent.“64% of senior leaders say big data is shifting the boundaries of traditional business.” Capgemini, Big & Fast Data: The Rise of Insight-Driven Business
Big data hiring or data-driven hiring is the latest in modernized recruitment. This is also known as people analytics and can provide a complete picture of a candidate. Important people data comes from all over – social media profiles, resume databases, performance reviews, business cards, political associations, and online behavior, such as shopping and reading preferences. The ability to mine all of this data and apply science to recruiting and hiring decisions can simplify the recruiter’s job. From time and cost savings to a reduction in attrition rates, the results of data-driven hiring are remarkable.
Sales, marketing, and operations are well-known for relying on big data analytics in making business decisions. Leveraging big data for recruiting and hiring is more recent, but no less important. According to a study performed by Capgemini, Big & Fast Data: The Rise of Insight-Driven Business, “65% of respondents see big data as a key enabler of their organization’s competitiveness, but only 27% describe their big data strategies as successful.”
In this article, we will discuss the art of big data recruiting, provide a comparative matrix of legacy ATS to Big Data solution features, and share the top 8 benefits that come with this modern hiring method.
Why is Big Data Recruiting Important?
Predictive analytics are used everywhere. Think about your online shopping, searching for a television show on Netflix, and booking travel. Isn’t it interesting that you can search for a new television on a website and then you visit Amazon and that same television appears on your homepage? This is predictive analytics. Today’s consumers expect a personalized experience and the likes of Amazon, Google, Zappos, and others are providing exactly that.
Finding employees can be an expensive and time consuming task for any organization. Finding the right employees, who will perform well and have longevity, is even more difficult. Incorporating big data into the recruiting process has been proven much more effective than traditional methods where every resume-qualified candidate is interviewed. Imagine spending months searching for the right employee to fill a vacant role only to find out just weeks after hiring that he/she is not going to work out. Big data can help an organization find the ‘right’ people much more quickly and reduce turnover, significantly impacting business success.
Who Within the Organization Finds Big Data Useful in Hiring?
Employers, big (enterprise) and small, benefit from big data recruiting. Recruiters, hiring managers, human resource staff, and staffing service personnel are increasing their reliance on big data in their recruiting and hiring process. According to a study performed by psychologists, Nathan R. Kuncel, Deniz S. Ones, and David M. Klieger, it was determined that “in hiring, algorithms outperformed instinct.” The analysis, appearing in the Journal of Applied Psychology in 2013, demonstrated that, “of 17 studies of applicant evaluations a simple equation outperforms human decisions ALONE by at least 25%, regardless of whether the job is on the front line, in middle management, or in the C-suite.”
In working on this article, we spoke with Kevin Wheeler, speaker, futurist, and founder of The Future of Talent Institute, who advises numerous organizations on big data talent management. Mr. Wheeler sees big data recruiting practices “increasingly used for high-volume jobs with clear requirements, such as when companies such as Target, Macy’s, or Best Buy are hiring a large number of sales representatives. Or, when a call center is hiring 100 people. In high-volume roles, data is commonly available from past hires, such as their speed to productivity and tenure. This data can be applied to the pool of candidates and will help predict who will be the best employees.”
Businesses Using Big Data Hiring
Gartner has seen a rise in inquiries associated with ‘data-driven,’ ‘evidence-based,’ and ‘data culture.’ According to the 2015 report, How to Establish a Data-Driven Culture in the Digital Workplace, this is a sign of organizations taking a more mature approach to information management.” In the same report, the analysts state that “both strategic and operational decision making are informed by data and analysis. These in turn drive velocity of business response and overall time-to-value, as well as influence transactional execution. Every data conversation needs to be framed in the context of being a business conversation, and every business conversation framed as a data conversation.”
Big data recruiting and predictive hiring practices are creeping into all industries. Companies, such as Redfin, Airbnb, ADP, Xerox, LinkedIn, Amazon, and Walmart have built their own predictive hiring capabilities in order to apply data intelligence to their hiring process. “Our goal is to never go to a campus again. We’ve moved from schools to skills,” says LinkedIn’s Director of Global Talent Acquisition, Tey Scott..
According to Wheeler, “Almost every big company is dabbling in big data for hiring, but companies whose databases have extensive amounts of data will have much better results than those with less data. This is where high-volume, retail associate hiring may be a better fit for data-driven hiring at this time, compared to a more specialized and scarce role of PHP developer.” The most important element for companies who successfully apply big data to their hiring is the consistency and accuracy of the data. “This is the biggest problem I deal with when working with big companies – lots of data, but it’s not clean. Some of the companies will hire a Data Scientist, but this is also a new role and qualifications are not completely clear. However, Brigham Young University has started graduating people with these specific Data Science degrees.”
Laszlo Bock, Google’s former VP for People Operations, performed extensive research and developed algorithms that help increase the probability of success when hiring candidates. Google is well known for their innovative hiring techniques and interview questions. With their huge year over year growth of close to 10,000 employees, quick and accurate hiring is a necessity.“G.P.A.’s are worthless as a criteria for hiring. We found that they don’t predict anything.”Laszlo Bock, Google's former VP for People Operations
The Relationship Between Big Data Recruiting and Building Talent Communities
A well-structured talent community augments the overall big data recruiting strategy. A talent community is much more than a list of qualified and available individuals in a database or spreadsheet who are seeking work. In fact, a talent community is most commonly managed by a recruiter or hiring manager and includes a network of recruiters, job-seekers, employers, employees, passive candidates, and others who share an interest in professional networking that is focused on recruiting and career. Talent communities interact in person, via email, newsletters, and social media. They communicate about business objectives and career goals, and cover topics from advice on career advancement, the best career sites, resume feedback, and sharing known employment opportunities. The key to building and maintaining a talent community is actively engaging your audience with social activities, regular interactions, and knowledge sharing in order to provide a quality experience. The ability to predict talent needs over the long term using big data can be enhanced by an established talent community that you can tap into when the need arises.
How Data-Based Recruiting Works
The use of big data across organizations has been a hot topic for several years. But, how is big data used by recruiters and hiring managers? Prior to big data technology, recruiters were limited to rigid resume databases and their immediate network of candidates. Now, data about prospective candidates is everywhere and it can be used to find the best contenders based on a multitude of factors. Data based recruiting activities include exploring LinkedIn and other social media sites, software solutions that aggregate internal company applicant data, and systems that gather large amounts of data and interpret it to provide intelligent insights that guide decision making. The human element and personal interactions remain important, such as responsiveness of a candidate to emails or phone calls, timeliness, and references. However, narrowing down results using scientific algorithms makes finding the right candidate easier, faster, and without 100% human bias.
When it comes to HR organizations successfully applying a big data strategy to recruiting, hiring, and retaining employees, Dwaine Maltais, HR tech veteran who focuses on big data experience and CEO and Co-Founder of Talentegy, finds that…Often times organizations see big data as a replacement for their data analytics strategy and try to fast track the process without building their core data and analytics foundation first. The best approach is to do the due diligence of identifying and validating all underlying datasources, both internal and external and then ensure that a basic set of metrics can be established. Then, the business can take advantage of the power of big data technology.
Benefits of Data-Driven Hiring
When big data is applied correctly to the recruiting and hiring strategy, benefits abound. LinkedIn found that, “talent acquisition teams with mature analytics are two times more likely to improve their recruiting efforts; and three times more likely to realize cost reductions and efficiency gains.”
Recruiters and hiring managers can use actionable insights to:
Top 8 Benefits of
#1 Save time and money by narrowing down candidates to only those who fit your profile and are available for employment. #2 Achieve competitive advantage with insight into competitive information, such as salary and benefits. #3 Increase employee retention with an improved chance of hiring staff with long term job success. #4 Reduce attrition by hiring candidates who fit your parameters and understanding what motivates, engages, and keeps them loyal. #5 Fill positions quickly without digging through mounds of unqualified candidates. #6 Reduce turnover by matching candidates with their dream position. #7 Predict success accurately with insights into past performance, demographics, and relationships. #8 Increase diversity with technology that supports impartial hiring.
Big data will not only help you understand your available candidates, but it can also help you prepare for your future needs. For example, data can help you estimate how long people stay in a certain role, therefore allowing you to predict future hiring needs and avoid over-hiring.
Challenges of Data-Driven Hiring
Besides inaccurate or non-existent data, the biggest challenges associated with data-driven hiring are ethics and privacy. For example, “passive analysis, such as looking at a candidates Facebook page to make a hiring decision can be questionable,” said Wheeler. Facebook, LinkedIn, and other social networking sites are great sources for personality and non-professional data, but is there a privacy line that is being crossed in the process? Data that is collected without candidate’s knowledge or consent and algorithms that use the data could lead to potential bias and profiling. In Talent Tech Lab’s Trends Report, Shon Burton, self-proclaimed geek and founder of HiringSolved, states that “Artificial Intelligence is good for pattern matching and prediction.” And, poses the question, “is it ethical to predict race, gender, honesty, intelligence, performance, reliability, or cultural fit? The question is not can we build this type of application, the question is should we?”
Early Generation Applicant Tracking Systems Compared to Big Data Hiring
With more searchable channels than ever before, finding the right candidate can be overwhelming.
An applicant tracking system is a software solution that automates recruiting and hiring activity. The system collects, organizes and tracks applicants, allowing recruiters to search for matches based on criteria such as years of employment, education level, and skillset. Though these systems continue to be heavily relied upon, they limit an organization’s ability to consistently find the best talent. The biggest downfalls include:
- Ignored applications.
- Manual processes.
- GPA or college rank cutoffs.
- Unstructured interviewing.
- “Mini-Me” hiring.
- Inability to engage candidates.
- Lack of data analysis to identify committed staff.
- Inability to reach passive candidates who are not actively seeking employment, or millennials who do not fill out lengthily online applications.
Compared to legacy database solutions that become overloaded with data that is not intelligently tied together or interpreted and must be extensively queried to find a match, big data analytical tools gather large volumes of diverse data from a variety of sources, and also provide broader insights into personality, performance, and competency that are found using both structured and unstructured data. Big data solutions tend to operate at a high velocity, with the ability to analyze data much more quickly than legacy applicant tracking systems (ATS). With big data predictive hiring solutions, you will experience:
- Ability to find more top performers.
- Lower turnover.
- Increased diversity.
- Shorter time to fill positions.
- Lower cost per hire.
Legacy Applicant Tracking Software Big Data
Manage applications x x Predict future hiring needs x Online resume submission x x Integration between ATS, social media, external job boards, resume databases x Identify top tier candidates in minutes x Evaluate personal attributes x Assess “fit” for the job x Predict performance x Collect and sort resumes x x Parse resumes x x Search resumes x x Find passive and active candidates x Deep search of websites, including Facebook, LinkedIn, and other social networking sites x Gather transactional information x x Interpret data points x Manual data entry x Proprietary query language x
Maltais has seen technology come a long way in a very short time. He says, “smart technologies, including solutions such as IBM Watson, Lexalytics, and Google DeepMind are accessible today beyond the scientific community with lower costs and simplified support of the underlying technology.” Maltais has been working with big data related to talent functions for a long time, before the concept of big data even existed. He is experiencing many solution providers utilizing big data in their various products, and “they are getting really good at aggregating data from internal talent functions and external sources. Leveraging all of this disparate data is a core component that helps drive data driven decisions.”
Talent Acquisition Solutions Entelo Fairygodboss GapJumpers Jopwell SparcStart Textio Talent Sonar (formerly Unitive) Koru HiringSolved Talentegy
Metrics Associated with Modern, Big Data Recruiting
Similar to other business units, recruiters and human resources teams need to demonstrate the value they bring to the business. Traditional metrics, such as cost per hire and time to fill only demonstrate how fast a position was filled while keeping costs down. These metrics do not demonstrate the quality of people hired and whether they will contribute to the growth of your company.
There are several key metrics / analytics that can be tracked and shared with business leadership to show contribution to business goals.
- Quality of hire – Look at performance reviews over time in order to benchmark employee quality across roles, recruiters, and business units.
- Offer acceptance rate – Evaluates the number of candidates presented with an offer with the percentage who accept the offer.
- Resignations and involuntary turnover within 90 days – Understand if you are selecting new employees who are a good fit.
- Performance by source – Visibility into where your best people are coming from.
- Retention rates – Identify roles that are hard to keep filled and understand why employees may be leaving.
How to Transform Hiring with Big Data
Incorporating big data into the hiring process can be a challenge, especially for recruiters who have focused on the people side of the business rather than data for their entire career. The Brandon Hall Group, an analyst and research organization focused on organizational performance, performed a talent acquisition benchmarking survey and found that the majority of organization, 64%, consider themselves ‘Casual’ – sourcing talent in a traditional method when the needs arise, and ‘Developing’- doing their best to identify and plan for needs, but with outdated and inconsistent processes. Only 8% consider their talent acquisition process ‘optimized’ – with appropriate planning, tracking, and assessments.
To begin integrating the power of big data in your process, you can:
- Analyze data to find out the channel your top talent used to enter your candidate pool.
- Look at your top talent’s geographic location.
- Identify the job categories your top candidates associate themselves with.
These attributes can help identify additional, similarly successful, and long term talent.
The Modern Recruiter
Traditional recruiters were expected to be good communicators, build relationships, and have exceptional people skills. While this continues to be important, the modern recruiter should have the following skills:
- Sales – ability to persuade passive and active prospects to apply, convince them to accept an interview, influence hiring managers to accept a candidate, and prove to a candidate that they should accept an offer.
- Proactive, strategic recruiting – Use data to predict future hiring needs and build talent communities to avoid shortages.
- Data analyst – Ability to interpret data from data scientists and make recommendations based on predictive analytics.
- Technological acumen – The ability to recommend technology solutions over costly new employees.
The ability to apply data is not simple for most recruiters or workforce managers. According to the 2014 LinkedIn Talent Solutions Survey, “77% of recruiters felt more efficient in their recruiting efforts when they have a solid understanding of the available talent pool.” At the same time, “75% of recruiters don’t use talent pool insights during meetings with hiring managers.” However, “71% of the recruiters would if they were easily available, sharable, and understandable.”
Other Important Elements of Hiring the Best Talent
Data driven hiring informs intelligent decision making, but it does not eliminate the need for human engagement. Social interactions and relationships are important and desired by both hiring managers and talent. Many workforce professionals encourage data-supported hiring because they believe the human element is necessary for engagement, capturing interest, and captivating candidates. In addition, millennials are less likely to spend time filling out lengthy applications
Technology spending has risen drastically over the past several decades. Technology to automate business processes, eliminate mundane human tasks, and more recently to intelligently find and hire the right talent using predictive big data hiring techniques are just a few areas that are high on the priority list. Wheeler suggests that “it is very early in the game for predictive recruiting, but it is effective and has a ton of potential. Unfortunately, we don’t understand all of the issues yet. We do know that in its current form it augments human judgement, but does not replace it.” Big data is not going away so why not use the massive amounts of information to your advantage? There is no question that access to intelligent data improves the hiring process. Isn’t the investment in finding loyal, innovative, high-performing, and satisfied employees worth the long-term growth your company will experience as a result?
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